1. Field of the Invention
The present invention relates to a method of image processing technology, and more particularly, to a method for auto-depicting (tracking) trends in object contours.
2. Description of the Prior Art
The method for depicting trends in object contours is considered to be a very important image processing technique. The reason is due to that more complete is the object contours depicted, more accurate the characteristics of the object, such as size, shape, or number, are recorded. These records may make the subsequent image processing be performed more easily and faster. The subsequent image processing refers to technologies that utilize the results of the edge detection for extended treatment such as scene analysis and pattern recognition. Regarding the technologies in practical applications, if we want to use less hardware resource or computing power to achieve better image processing performance, the edge detection results of the input image will inevitably need to have a higher usability. However, in a case where many image processing processes do not use the results obtained by depicting trends in object contours, but only use edge detection results as the input of the subsequent image processing, the results of the subsequent image processing is likely to be worse than expected. Since the existing edge detection methods usually retain only the discontinuous or representative edge segments, the correspondent relationship between these edge segments is not retained. For example, it is not informed that two segments belong to a discontinuous edge of the same object contour while performing the edge detection. As a result, the complete object contour can not be created. Thus, to identify the continuity of a plurality of edge segments under the condition that edge segments are discontinuous and then generate a possible object contour in accordance with the continuity established based on the edge segments, the present invention therefore proposes a method for depicting trends in object contours.
The conventional method for depicting trends in object contours is as follows: first, selecting a start point from an input image, where the start point is any pixel corresponding to the edge; detecting surrounding edge pixels of the start point and taking a pixel with a coordinate closest to the start point and not on the same edge where the start point is located; taking an edge containing the closest edge point as the object contour that must be depicted. However, the conventional method of selecting the closest edge for depicting trends in object contours has certain shortcomings. For example, when the background of the input image is complex, there is noise interference, and/or there is changing light and shadow, this could easily lead to the case of deviation or error of the depicted trends in object edge/contour. As shown in FIG. 7, if the conventional method which selects the closest edge is applied to scattered edges, the edge in the gray rectangle is taken as the object contour needed to be depicted. In other words, the conventional method which selects the closest edge is not robust enough, and is prone to be affected by the small difference of the input image (e.g., the light source) to therefore make the depicting result not properly fit the trends in object contours and even take the edges which belong to different contours to be the same trend in the object contour.
Related prior patents, such as Japanese Patent Publication No. 2001-319239, propose a method for tracking human contours. The method first supposes that a target pixel is located at the edge and there is an interval in front of the target pixel to act as the intensity range for retrieving the edge. When the edge intensity value within the interval is higher than a predetermined threshold, then the coordinate of the maximum edge intensity value within the interval is regarded as the coordinate of the next target pixel. However, the method for tracking contours of a character only uses the edge intensity value as the basis for determining the coordinate position of the next target pixel. When the background of the input image is more complex (e.g., the background includes woods, bushes, etc.) or the noise interference is severe, the coordinate position of the next target pixel is prone to be wrong.
In view of this, the present invention pays attention to drawbacks of the prior art design, and therefore proposes a method for auto-depicting trends in object contours to effectively overcome the above-mentioned issues.